Keynote speaker: Visualization for deep learning training
Tzi‐cker Chiueh · 2016
Summary form only given. The enormous successes of deep learning in many domains such as video, audio, speech, text, sequence, etc. has swept the academia and industry alike, to the extent that many are touting deep learning training as an alternative form of programming future applications. Amid this excitement lies a more sombre question: if training for deep learning models is compared to software coding, what is the integrated development environment (IDE) for deep learning training? Specifically, what are the debugging and analysis tools required for manually refining and evolving a deep learning model towards its final form? In this presentation, I will survey related work in this area and outline the visualization requirements of a deep learning IDE that we are currently working on.